Porting a Ray Tracer to Rust, part 1

Tue Dec 30, 2014

I’ve decided to port over my physically based ray tracer tray to Rust to finally try out the language with a decent sized project. In the series we’ll work through the implementation of a physically based ray tracer built on the techniques discussed in Physically Based Rendering. I won’t go into a lot of detail about rendering theory or the less exciting implementation details but will focus more on Rust specific concerns and implementation decisions along with comparisons vs. my C++ version. If you’re looking to learn more about ray tracing I highly recommend picking up Physically Based Rendering and working through it. Hopefully throughout the series folks more experienced with Rust can point out mistakes and improvements as well, since I have no experience with Rust prior to this series.

With the intro out of the way, let’s get started! Since it’s the beginning of the series this is my first time really working with Rust and our goal is pretty simple: render a white sphere and save the image.

The Linear Algebra Module

I started by porting the linear algebra module used by tray over, since almost everything else we do in the ray tracer will need basic linear algebra operations. This was pretty straightforward but I did run into a few minor annoyances with things in the current state of Rust, rustc 0.13.0-nightly (636663172 2014-12-28 16:21:58 +0000), namely: lack of function overloading , default parameters and operator overloading for both left and right multiplication.

Function Overloading

This is a feature I used extensively throughout the C++ version of the ray tracer which helps make things a bit more ergonomic. I first ran into this when implementing my vector type. In tray I have overloads for the constructor so that it can be constructed with x, y and z all set independently or by setting them all to the same value, as below.

Vector(float x, float y, float z) : x(x), y(y), z(z) {}
Vector(float x) : x(x), y(x), z(x) {}

This is convenient as there are many times when you simply want a vector that’s initialized to all 0 or 1 for example. Since function overloading isn’t currently supported in Rust these two methods require different names, I chose broadcast for my single value constructor.

pub fn new(x: f32, y: f32, z: f32) -> Vector {
    Vector { x: x, y: y, z: z }
pub fn broadcast(x: f32) -> Vector {
    Vector { x: x, y: x, z: x }

I’d really prefer to just have an overload of new(x: f32) -> Vector which performed the same construction that broadcast does currently, although this is a relatively minor annoyance.

Default Parameters

This relates closely to function overloading in that it also simplifies commonly written calls, eg. my C++ vector constructors also default to set the values to 0, so constructing a vector of all 0 values is simply Vector{}. This doesn’t seem to be currently in Rust, but is another (somewhat minor) feature that would be nice to have.

Overloading Left and Right Multiply

While it was very easy to overload the vector * scalar operator, writing the same overload for scalar * vector doesn’t seem to be possible (please let me know if this has changed!). On the topic of operator overloading, I do really like Rust’s decision to make them traits because they can then be set as requirements for generic functions. Below is my vector * scalar overload, it’s two extra lines than in C++ but is very clear to read.

Edit (12/31/14): ben0x539 mentioned that unsupported left-multiply overloading is a bug which may be getting fixed in 19434.

impl Mul<f32, Vector> for Vector {
    fn mul(self, rhs: f32) -> Vector {
        Vector { x: self.x * rhs, y: self.y * rhs, z: self.z * rhs }

Edit (5/9/15): Overloading left and right multiply is now supported in Rust. Additionally the method for writing overloaded operators has changed significantly with the addition of associated types. The current implementation of right and left multiply for Vector are now:

// Multiply a vector by a f32 on the right, eg. `vec * 2.0`
impl Mul<f32> for Vector {
    type Output = Vector;
    /// Scale the vector by some value
    fn mul(self, rhs: f32) -> Vector {
        Vector { x: self.x * rhs, y: self.y * rhs, z: self.z * rhs }

// Multiply a f32 by a vector on the right, eg. `2.0 * vec`
impl Mul<Vector> for f32 {
    type Output = Vector;
    /// Scale the vector by some value
    fn mul(self, rhs: Vector) -> Vector {
        Vector { x: self * rhs.x, y: self * rhs.y, z: self * rhs.z }

Because operator overloading is done through traits we can set constraints on generic functions to require that the types being worked on implement certain operations. This makes the function clearer than in C++ (eg. what types it takes) and also gives much better compilation errors when types not implementing the required operations are passed. For an extremely simple comparison lets look at the C++ and Rust implementations of lerp.

template<typename T>
T lerp(float t, const T &a, const T &b){
    return a * (1.f - t) + b * t;

If we misuse the lerp implementation in C++ we get a decent amount of errors. gcc-4.9 is quite clear about what went wrong, but these errors are shown as occuring inside the function call (since that’s the point of error) and would be harder to parse for more complex functions.

test.cpp: In instantiation of ‘T lerp(float, const T&, const T&) [with T = Foo]’:
test.cpp:10:32:   required from here
test.cpp:3:30: error: no match for ‘operator*’ (operand types are ‘float’ and ‘const Foo’)
     return (1.f - t) * a + t * b;
test.cpp:3:22: error: no match for ‘operator*’ (operand types are ‘float’ and ‘const Foo’)
     return (1.f - t) * a + t * b;
test.cpp: In function ‘T lerp(float, const T&, const T&) [with T = Foo]’:
test.cpp:4:1: warning: control reaches end of non-void function [-Wreturn-type]

As a user glancing through some template code in C++ it may not be clear what operations and functions the type must provide (although for a simple lerp it is). Rust solves this by allowing you to specify requirements on the traits implemented by the types. In lerp we need to be able to multiply the types by floats, add the types to each other and make a copy of them to return. Specifying these requirements up front makes the function interface much clearer:

pub fn lerp<T: Mul<f32, T> + Add<T, T> + Copy<T>>(t: f32, a: &T, b: &T) -> T {
    *a * (1.0 - t) + *b * t

If we misuse the lerp implementation in Rust we get some pretty clear and helpful errors, telling us why the error occured and what we should do to resolve it. The error messages also point us to the location of the bad call, which is much more useful than being pointed at a problem inside some template function. Note that in C++ we also didn’t get any errors about the lack of operator+, which we’d get next if we fixed our missing operator*.

tray_rust/src/main.rs:11:15: 11:27 error: the trait `core::kinds::Copy` is not implemented for the type `Foo`
tray_rust/src/main.rs:11     let awd = linalg::lerp(0.5, &Foo, &Foo);
tray_rust/src/main.rs:11:15: 11:27 note: the trait `core::kinds::Copy` must be implemented because it is required by `tray_rust::linalg::lerp`
tray_rust/src/main.rs:11     let awd = linalg::lerp(0.5, &Foo, &Foo);
tray_rust/src/main.rs:11:15: 11:27 error: the trait `core::ops::Add<Foo, Foo>` is not implemented for the type `Foo`
tray_rust/src/main.rs:11     let awd = linalg::lerp(0.5, &Foo, &Foo);
tray_rust/src/main.rs:11:15: 11:27 note: the trait `core::ops::Add` must be implemented because it is required by `tray_rust::linalg::lerp`
tray_rust/src/main.rs:11     let awd = linalg::lerp(0.5, &Foo, &Foo);
tray_rust/src/main.rs:11:15: 11:27 error: the trait `core::ops::Mul<f32, Foo>` is not implemented for the type `Foo`
tray_rust/src/main.rs:11     let awd = linalg::lerp(0.5, &Foo, &Foo);
tray_rust/src/main.rs:11:15: 11:27 note: the trait `core::ops::Mul` must be implemented because it is required by `tray_rust::linalg::lerp`
tray_rust/src/main.rs:11     let awd = linalg::lerp(0.5, &Foo, &Foo);

C++ also provides default implementations of the copy constructor for types while Rust does not, thus in Rust we must require that Copy is implemented for the type. I think Rust’s decision to not provide copy by default is a good one as it can cause trouble if you forget to delete the copy constructor and copy-assign operators in C++ and your type should not be copied. For most types that should be copyable that I’ve worked with so far it’s simple enough to just use a compiler generated implementation via #[deriving(Copy)].

Rust’s Module System

In tray I chose to split up the various components of the ray tracer into their own libraries which are then statically linked into the main executable. This design is also possible in Rust by splitting functionality up into independent modules. I had some difficulty initially understanding how to work with modules and how inter-module dependencies worked but after reading through the guide the end result is very nice. tray_rust is organized with most functionality implemented in separate modules that are built into a library and used by main.rs to render the image.

Under src I have the default executable and library files, main.rs and lib.rs. Also under src are the various module subdirectories, eg. linalg for the linear algebra module, each containing a mod.rs which defines some module level functions and re-exports the sub-modules implementing other functionality, such as the vector module in linalg. The end result of this is that I can have a very simple lib.rs which just publicly exports the various modules:

pub mod linalg;
pub mod film;
pub mod geometry;

In main.rs I can then tell Rust I need to build and link against the default library crate for the executable, tray_rust which is defined by lib.rs, and use the modules:

extern crate tray_rust;

use tray_rust::linalg;

fn main() {
    let v = linalg::Vector::new(1.0, 2.0, 3.0);
    println!("Hello! {}", v);

Inter-module dependencies and circular dependencies are also handled very nicely. In the geometry module if I need access to some of the types in linalg I can simply use linalg; and not need to worry about dealing with fiddly link order requirements. Circular dependencies aren’t a problem at all, which is nice coming from C++ where they can be a bit annoying, requiring forward declarations and such.

Re-exporting From Modules

I initially struggled with the sheer amount of typing required for some of the nested modules. Since my Vector struct is in the vector module within the linalg module to access it I would have to type linalg::vector::Vector, which is a mouthful. While important to avoid naming conflicts I thought this was pretty excessive and after some googling stumbled onto re-exporting from modules. This lets us re-export the Vector type from the linalg module allowing us to use it as linalg::Vector, which I think is more than enough to avoid name conflicts. This is done in the linalg module file, linalg/mod.rs where we export the various sub-modules and re-export their types:

pub use self::vector::Vector;

pub mod vector;

Working With Traits

In my C++ ray tracer geometry is defined by an interface that provides methods such as intersect which tests a ray for intersection with some piece of geometry, making it very easy to add new geometry types to the ray tracer by implementing the interface. Additionally we separate the definition of some geometry with its occurance in the scene, so that a single model may appear multiple times in the scene with different materials and transformations, a method known as instancing. To keep things simple when implementing our bounding volume hierarchy our instance type also implements the geometry interface, simply transformating the ray into object space and then calling the geometry’s intersect method.

class Geometry {
    virtual bool intersect(Ray &ray, DifferentialGeometry &dg) const = 0;

This technique carries over directly to Rust in the form of traits. Instead of providing a base class with pure virtual methods like we’d do in C++ we define a Geometry trait that provides these same methods and write implementations for our geometry such as our Sphere type. Below is the geometry trait implemented by the various scene geometry types in tray_rust.

pub trait Geometry {
    fn intersect(&self, ray: &mut linalg::Ray) -> Option<DifferentialGeometry>;

intersect has an interesting return type, which lets me talk about another cool feature of Rust: no null pointers! Instead Rust defines an Option<T> type which can be either Some(T) or None and both cases must be considered. In C++ (and C, Java, etc) it’s easy to ignore the possibility that a pointer may be null resulting in seg faults, null pointer exceptions and more. Rust avoids the billion dollar mistake by forcing you to not be sloppy.

In my C++ version I would take the DifferentialGeometry as a mutable reference and return a bool if the ray intersected the object, filling out the differential geometry with the hit info if it hit. In Rust this is expressed much cleaner, if there’s a hit we return Some(DifferentialGeometry) otherwise we simply return None. The DifferentialGeometry also needs to send back information about the instance and geometry that was hit, leading to the next topic: lifetimes in Rust.

Lifetimes in Rust

The concept and enforcement of ownership in Rust was one of the features that initially got me interested in the language. For the most part lifetimes are implicit in the language, however sometimes the compiler needs some assistance deducing lifetimes for some variables. I first encountered this when writing my DifferentialGeometry struct which needs to return back references to the hit Geometry and Instance so we can shade the hit point properly. In order to verify the code is valid the compiler needs to check that the geometry and instance referenced by the differential geometry will not be outlived by the differential geometry, as this would result in dangling references. To specify this separate lifetime on a struct we’d write:

pub struct DifferentialGeometry<'a> {
    // This isn't quite correct yet!
    pub geom: &'a Geometry,

Error: Explicit Lifetime Bound Required

Writing the above geom member resulted in the most difficult error message I encountered so far in Rust. Attempting to compile the above results in:

src/geometry/differential_geometry.rs:17:19: 17:27 error: explicit lifetime bound required
src/geometry/differential_geometry.rs:17     pub geom: &'a Geometry,

The message is actually quite clear, if I knew what an explicit lifetime bound was. However it doesn’t seem to be mentioned in the guides which is what made resolving this error much more challenging than previous ones. After a decent amount of googling I found that while the way I wrote geom is correct for a regular struct a trait requires an explicit lifetime bound since the type of data being referenced is unknown (we only know it implements the trait). This is resolved by bounding the lifetime with Geometry + 'a and the correct form is:

pub struct DifferentialGeometry<'a> {
    pub geom: &'a (Geometry + 'a),

I’d like to find some more information on what exactly this means, such as what a lifetime bound tells the compiler and how it’s used. Unfortunately I didn’t have much luck finding information on this, if anyone has some links please do let me know.

Edit (12/31/14): @JakeGoulding pointed me to one of his answers on stack overflow which I found to be helpful. Another answer linked in the thread also has a really nice explanation. As a result of reading the answers I’ve changed the geom member’s type to &'a (Geometry + 'static) to require the object implementing the trait that we’re referring to be a struct, since we won’t be implementing Geometry for reference types.

A Poor Design Choice

The DifferentialGeometry struct also contains a design decision that I’m not very happy with. The differential geometry is initially created within the geometry that was hit, since it doesn’t know about the instance that is using it that was hit it’s not able to set the instance member. This results in the instance member of DifferentialGeometry having to be written as an optional reference, when really it’s not optional. Any geometry we hit is associated with an instance, it’s just that we don’t know which at the time of hitting the geometry itself, we need to go back up the call stack to the instance that called the geometry’s intersect method. This results in the DifferentialGeometry struct being written as:

pub struct DifferentialGeometry<'a, 'b> {
    pub p: Point,
    pub n: Normal,
    pub ng: Normal,
    pub geom: &'a (Geometry + 'a),
    pub instance: Option<&'b Instance<'b>>,

Within the Sphere’s implementation of Geometry::intersect we know the geometry and hit information but not the instance and thus if the sphere is intersected we return:

Some(DifferentialGeometry::new(&p, &n, &n, self, None))

Then in the instance using the geometry we see that it was hit and transform the DifferentialGeometry back into world space and set the instance:

impl<'a> Geometry for Instance<'a> {
    fn intersect(&self, ray: &mut linalg::Ray) -> Option<DifferentialGeometry> {
        let mut local = self.inv_transform * *ray;
        let mut dg = match self.geom.intersect(&mut local) {
            Some(dg) => dg,
            None => return None,
        ray.max_t = local.max_t;
        dg.p = self.transform * dg.p;
        dg.n = self.transform * dg.n;
        dg.ng = self.transform * dg.ng;
        dg.instance = Some(self);

One option is to give Instance its own intersect method and have the Geometry intersect function just return back the hit point information and have the Instance fill out the geometry and instance references. This isn’t such a good option though since it breaks the illusion that instances are just geometry and will cause trouble when trying to write a bounding volume hierarchy that we can put the instances in the scene into and can also use to construct BVHs on triangle meshes to accelerate intersection testing.

As far as the end user of the intersect call is concerned there will always be a geometry and instance reference on the DifferentialGeometry returned but I’m not sure how to express this. Another possibility would be to have another Intersection type which didn’t have the option and could be constructed from an Option<DifferentialGeometry> and would return None if the DifferentialGeometry or the instance was None (although the latter wouldn’t happen), otherwise it would unwrap the instance member’s option and return Some<Intersection>. I’ll probably look into implementing this as the cleanest solution I can think of even though it’s really just a band-aid. If anyone has some ideas or suggestions, please leave a comment or get in touch on Twitter or IRC (I’m Twinklebear on freenode and moznet).


Rust also has built in support for specifying tests and benchmarks by placing #[test] or #[bench] attributes respectively. These are then run using Cargo with cargo test or cargo bench. This built in support makes it very easy to write and run unit and integration tests for your code and is really convenient coming from C++ where testing is done through third party libraries.


Rust comes with a built in documentation generation tool that makes it really easy to have nice documentation for both the language and user libraries by just running cargo doc on your crate. Since the generated doc site is all static pages it’s simple to host them on Github pages or browse them locally. For example here is the rustdoc for this project. Good documentation is critical for any library or decent sized project and having it standardized and built into the language like this will hopefully improve the overall quality of documentation for user libraries.

Putting it all Together

Now that we’ve got modules to handle linear algebra, geometry and camera/image operations we have everything we need to render a sphere! In main.rs we create our render target, camera and sphere then attach the sphere to an instance and loop over the pixels in the image, firing rays through each and checking for intersections:

extern crate tray_rust;

use tray_rust::linalg;
use tray_rust::film;
use tray_rust::geometry;
use tray_rust::geometry::Geometry;

fn main() {
    let width = 800u;
    let height = 600u;
    let mut rt = film::RenderTarget::new(width, height);
    let camera = film::Camera::new(linalg::Transform::look_at(
        &linalg::Point::new(0.0, 0.0, -10.0), &linalg::Point::new(0.0, 0.0, 0.0),
        &linalg::Vector::new(0.0, 1.0, 0.0)), 40.0, rt.dimensions());
    let sphere = geometry::Sphere::new(1.5);
    let instance = geometry::Instance::new(&sphere,
        linalg::Transform::translate(&linalg::Vector::new(0.0, 2.0, 0.0)));
    for y in range(0, height) {
        for x in range(0, width) {
            let px = (x as f32 + 0.5, y as f32 + 0.5);
            let mut ray = camera.generate_ray(px);
            match instance.intersect(&mut ray) {
                Some(_) => rt.write(px.0, px.1, &film::Colorf::broadcast(1.0)),
                None => {},
    film::write_ppm("out.ppm", width, height, rt.get_render().as_slice());

The executable and library modules are built and the executable run with cargo run. While the resulting image isn’t very impressive, we’re well on our way to writing a flexible physically based ray tracer.

Final Thoughts

While I did encounter some minor annoyances with Rust I’m really happy with how the language is shaping up as it nears 1.0 and look forward to the 1.0 release. One other difference compared to C++ I didn’t mention is that variables in Rust are immutable by default and must be explicitly declared mutable whereas C++ defaults to mutable variables. I think Rust’s decision of immutable by default is great, most of the time I find that I really only need a few mutable variables in my programs while everything else is constant or locally constant and used to compute other constant results or operate on the few mutable variables.

Until Next Time

In the next post I’ll discuss the process of making tray_rust multithreaded and adding support for some simple materials and lights which we’ll then render using Whitted recursive ray tracing. While this ray tracing method doesn’t account for global illumination like path tracing or photon mapping it’s simple to implement and very fast and will help us develop and test our abstractions for integrators, materials and lights.

If you have comments, suggestions for improvements or just want to say “hi” feel contact me on Twitter. The code for the Rust ray tracer is MIT licensed and available on Github.